1. Field of the Invention
The present invention relates to an information recording and reproducing apparatus such as a magneto-optical recording and reproducing apparatus or an optical recording and reproducing apparatus for reproducing information by means of an optical head, and relates particularly to a partial response method suited for use in combination with a Viterbi decoder for high density recording with an improved error correction rate.
2. Description of the Related Art
Partial response techniques have been proposed to replace peak detection (level detection) type signal detection methods as a means of improving the high density recording capacity of the recording and reproducing signal processing technologies in digital magnetic recording. These partial response techniques have been described, for example, in Japanese TOKKAI H4-221464 (1992-221464) and H5-2842 (1993-2842). It is also known that applying Viterbi decoding techniques to the demodulation system as a maximum likelihood decoding method (error correction decoding) is an effective means of improving the error rate characteristic. Partial response and Viterbi decoding have also been applied in the related field of optical recording and magneto-optical recording as described by Ozawa, Yamauchi, and Tazaki in "Applications of Viterbi decoding using a new variable length block coding and d constraint for magneto-optical recording" (pp. 1369.about.1375, Television Magazine (in Japanese), 44, 10 (1990)).
FIG. 11 is a block diagram of a conventional magneto-optical recording and reproducing system using partial response and Viterbi decoding.
To suppress interference (intersymbol interference) of the elementary waveform (readback waveform) as a result of the bandwidth limit of magneto-optical drive 3, and to facilitate extraction of the synchronization data from the elementary waveform sequence in this magneto-optical recording and reproducing system, a specific coding modulator 1 is provided for coding according to coding rules matching the characteristics of magneto-optical drive 3. This coding modulator 1 comprises a (2,7) RLL coder for RLL-coding (run-length-limited coding) the input data bit sequence {A.sub.i } (a digital information sequence) to be recorded using the minimum run constraint d=2 and maximum run constraint k=7; and an NRZI modulator for converting the (2,7) RLL code sequence to an NRZI (non-return-to-zero inversion) code (at symbol 0, level inversion is not applied; only at symbol 1 is level inversion applied at the leading edge of the cell). Constraint k (=7) of the (2,7) RLL code rule offers the advantage of being able to suppress intersymbol interference. In addition, the mark length modulation by an NRZI modulator helps to improve the recording density.
Furthermore, with the magneto-optical recording and reproducing system shown in FIG. 11, the coded data sequence {a.sub.i } generated by coding modulator 1 is first input to a precoder 2 at a certain position. Precoder 2 has a transfer characteristic that is the inverse of that of the waveform equalizer 4 described below, specifically a [1/(1+D)]mod2 characteristic. Precoding by precoder 2 cancels the recording and reproducing characteristics in the output of the waveform equalizer 4 to prevent error propagation by Viterbi decoder 7 on the output side.
The recording code sequence {d.sub.i } from precoder 2 is then recorded to the magnetic thin-film of the magneto-optical recording medium as the elementary waveform sequence to be recorded using the thermal effect of the semiconductor laser of magneto-optical drive 3.
During the reproduction process, the recorded symbol sequence is read from the magneto-optical recording medium by the optical head of magneto-optical drive 3, and amplified by a preamplifier to obtain readback elementary waveform sequence e(t).
Waveform equalization is then applied to the elementary waveform sequence e(t) by the waveform equalizer 4 to correct the waveform and compensate for waveform interference as a means of achieving high density recording. A transversal filter is generally used for this waveform equalizer 4. As shown in FIG. 12, this filter comprises a serial delay stage (SR) of (2L) serially-connected delay circuits 4a having a delay time T; (2L+1) weighting circuits (multipliers) 4b for multiplying the output from each tap (signal discrimination point) by a weighting coefficient c.sub.j (where j=-L, . . . , -1, 0,+1, . . . ,+L); and an adder 4c for obtaining the total sum of the weighted products. Note that it is not necessary for the delay time T of the delay circuits 4a to be equal to the cell width T.sub.b of the NRZI encoded sequence, and delay circuits 4a of delay time T=T.sub.b /m (where m is a natural number), for example, may be used to reduce waveform equalization error.
When the readback elementary waveform stream e(t) is sampled at the optimum sampling instant kT.sub.b, the sampled values are dependent only on the elementary waveform corresponding to the coded symbol. To eliminate interwaveform interference and prevent interference from adjacent elementary waveforms, the first Nyquist condition for zero intersymbol interference (shown below) must be satisfied. EQU e.sub.k =e(kT.sub.b)=e.sub.0 .delta..sub.k0 [1]
where T.sub.b is the cell width (the time ufiit of the NRZI encoded sequence); and .delta..sub.k0 is the Kronecker delta where .delta..sub.ij =1 (when i=j), and .delta..sub.ij =0 (when i.noteq.j) A rectangular pulse wave, Nyquist waveform, and other waves are elementary waveforms e.sub.0 known to satisfy this Nyquist condition, but the most basic waveform known to satisfy the Nyquist condition is the Nyquist waveform (sampling function) r(t) shown below. EQU r(t/T.sub.b -n)=sinc (t/T.sub.b -n)=sin (t/T.sub.b -n)/(t/T.sub.b -n)[2]
However, because resolution deteriorates in high density recording and differences in precision occur between different devices even when the Nyquist waveform r(t) is used as the elementary waveform, interwaveform interference unavoidably continues to occur and induces intersymbol interference. Thus, waveform equalizer 4 actually actively uses interwaveform interference. In other words, if h(t) is the output waveform (impulse response waveform) of waveform equalizer 4 to the combined transfer functions of precoder 2, magneto-optical drive 3, and waveform equalizer 4 when an impulse is applied to the input of precoder 2, the output x(t) of waveform equalizer 4 to an encoded data sequence {a.sub.i } input to precoder 2 is obtained by equation [3]. ##EQU1## where a.sub.k is the data input at time k, and T=T.sub.b.
If waveform equalizer 4 is a transversal filter having delay circuits 4a of delay time T as shown in FIG. 12, h(t) is expressed by a convolution of Nyquist waveform r(t). ##EQU2##
where the Nyquist waveform is equivalent to the response component of the delay operation when n.noteq.0, and is known as the partial response. From equations [3] and [4], ##EQU3## and, can be detected as EQU x(t=kT.sub.b)=a'.sub.n .vertline..sub.mod N [ 7]
from equation [1]. PA1 where PR.sub.11 (f) is the transfer function for PR(1,1). If a delay operator D=exp(-j.omega.T.sub.b) is used, PR(1,1) can be digitally expressed as G(.omega.)=(1+D) where .omega.=2 .pi.f. Thus, for transfer function PR.sub.11 (f), .vertline.G(f).vertline.=.vertline.2 cos (.pi.fT.sub.b).vertline. where the cut-off frequency f.sub.11 =1/2T.sub.b.
In other words, output x(t) of waveform equalizer 4 is discriminated at a discrete-time discrimination point (kT.sub.b) as a multivalued signal level of (mod N). In general, the weighting coefficients c.sub.j are set at an appropriate integral ratio. A waveform equalizer 4 of which the weighting coefficients c.sub.j are an integral ratio is known as a partial response (PR) circuit. In the partial response method, the output of the PR circuit is generally expressed as PR(c.sub.o, c.sub.1, . . . , c.sub.L) using the weighting coefficients c.sub.j of the PR circuit. Note that the weighting coefficients c.sub.j may be expanded to include real numbers as necessary. Note, also, that Kretzmer, the developer of the PR method, shows five forms for the PR method: PR(1,1), PR(1,2,1), PR(2,1,-1), PR(1,0,-1), and PR(-1,0,2,-1).
The optical transfer function OTF of magneto-optical recordings suggests a sinc function in the magneto-optical recording and reproducing system shown in FIG. 11, which therefore uses the PR(1,1) method having similar frequency characteristics.
Because c.sub.o =c.sub.1 =1 in the PR(1,1) method, the output waveform (impulse response) h(t) of waveform equalizer 4 is a composite waveform of r(t/T.sub.b) and the delay waveform r(t/T.sub.b -1). The amplitude value thus changes 0.fwdarw.1.fwdarw.1.fwdarw.0 because the discrimination point is every T.sub.b, and the impulse input can therefore be detected by discriminating the amplitude value. When delay operator D is used in the PR(1,1) method, digital transfer function G(D) can be expressed as G(D)=1+D. Thus, an input of d.sub.k results in an output expressed as (d.sub.k +d.sub.k-1). When d.sub.k =d.sub.k-1 =1, the output is 2, and the output level of waveform equalizer 4 is a trivalue output of (0, 1, 2).
The PR method actively uses a waveform having a nonzero response (correlative waveform) to a single stored elementary waveform at plural discrimination points of the readback signal. As a result, the PR method detects the correlation of the constant time change of a level even when there is interwaveform interference, and is known as an equalization method appropriate to the recording and reproducing characteristics of level-correlated encoding such as (2,7) RLL encoding.
Next, white noise added during the readback and equalization processes is removed from the output x(t) of waveform equalizer 4 (FIG. 11) by low pass filter (LPF) 5. The signal is then sampled by A/D converter 6 at a discrete-time point of the cell width, and the sampled values are quantized.
It should be noted that noise is added by waveform equalizer 4, and is actually output as an error series. The readback digital signal quantized by A/D converter 6 is then processed by Viterbi decoder 7 using a maximum-likelihood (ML) decoding method applying the Viterbi algorithm.
ML decoding does not process each signal value at each discrimination point during the discrimination and decoding process, but processes a signal series of a finite length (constraint length). The Viterbi algorithm is one type of ML decoding method, more specifically a sequential trellis search algorithm for ML sequence detection, and assumes that the received (readback) signal sequence can be expressed by a finite automaton model. The transversal filter waveform equalizer 4 shown in FIG. 12 is also a so-called convolution encoder, and the output therefrom can be expressed as a finite automaton model (a machine whereof the output is determined by the internal state and input). The Viterbi algorithm obtains the path (internal state transition path) whereby the metric (likelihood standard) input at each time point is lowest at each time transition point of the trellis diagram (a diagram showing the output code series generated by a state change process of the encoder according to the input information series) of a finite state machine encoder.
With the magneto-optical recording and reproducing system shown in FIG. 11, Viterbi decoding is used to decode the combination of (2,7) RLL and PR(1,1) encoding. If magneto-optical drive 3 and waveform equalizer 4 are treated as a finite state machine (convolution encoder), the corresponding state transition diagram for their internal states is shown in FIG. 13. The input information series is output d.sub.t (=0, 1) of precoder 2, and the output code series is output x.sub.t of waveform equalizer 4. Waveform equalizer 4 is the PR(1,1) circuit, and the detected output x.sub.t therefrom is 0, 1, or 2. Furthermore, because it comprises only one delay element, there are 2.sup.1 =2 internal states. If the internal state is expressed as u.sub.t-1, internal state u.sub.t-1 =0 corresponds to state S.sub.1, and internal state u.sub.t-1 =1 corresponds to state S.sub.2. Note that when the internal state is S.sub.1, state S.sub.1 is held when the input is 0, and the output is therefore 0. As shown in FIG. 13, the input/output relationship d.sub.t /x.sub.t is expressed as 0/0. When the input is 1, the internal state shifts to state S.sub.2, and the output is 1. When input 1 is input to state S.sub.2, state S.sub.2 is held and the output is 2. When input 0 is input, the internal state shifts to state S.sub.1, and the output is 1.
FIG. 14 is a trellis diagram of the time-based internal state changes based on the state transition diagram shown in FIG. 13. In FIG. 14, the dotted directed lines show the transition resulting from input 0, and the solid directed lines show the transition resulting from input 1; the d.sub.t /x.sub.t relationship is shown on each directed line. Simply stated, the Viterbi algorithm first calculates the metrics of plural branches merging at each time point (t-2.about.t+2), using, for example, the Hamming distance as the branch metric. The path with the smallest branch metric is then saved as the survivor path. If there is more than one path with the same branch metric, any one of the paths may be selected. Because the initial state, the constraint length (which is a guide to the correlation of the encoded sequence), and the final state are known to the demodulation side, it is possible to trace the history of the survivor path from the unique final state to arrive at a unique initial state, and thereby determine the most probable path. By thus considering the correlation of state transitions, it is possible to overcome bit errors in the magneto-optical drive 3 and waveform equalizer 4, and the correct (accurate) information series can be demodulated.
A general description of the configuration of a Viterbi decoder 7 is given below. As shown in FIG. 15, a general Viterbi decoder comprises a hypothetical path memory 7a for storing the expected value obtained from the waveform of a data series of a bit count corresponding to the constraint length; an ACS circuit 7b comprising an adder (A), comparator (B), and selector (C), and obtaining by means of adder (A) the sum of the pre-calculated path metric and the square of the difference of the sample value from A/D converter 6 and the expected value from the hypothetical path memory 7a, comparing the additive outputs by means of comparator (C), and then selecting the smaller value by means of selector (C); a path memory 7c for storing the last values of the selected hypothetical paths; and a path selector 7d for selecting the path with the smallest path metric, and outputting the data at the tail end of the path as the demodulation data.
Demodulator 8 located at the last stage of the system shown in FIG. 11 demodulates the error correction code {a.sub.i } obtained from Viterbi decoder 7 to restore the information sequence {A.sub.i }, and thus effectively inverses the conversion applied by (2,7) RLL and NRZI encoding.
The following problems are presented by the magneto-optical recording and reproducing system described above.
(1) If the transfer function of recording and reproducing system magneto-optical drive 3 in the magneto-optical recording and reproducing system shown in FIG. 11 is H(f), and the transfer function of waveform equalizer 4 is E(f), it is necessary to determine the weighting coefficients c.sub.j of waveform equalizer 4 necessary and sufficient to satisfy equation [8] below for PR(1,1) partial response coding. EQU H(f).multidot.E(f)=PR.sub.11 (f) [8]
FIG. 16 is a graph of the frequency characteristics of a transfer function with a low recording density. Because the recording density is low, the cut-off frequency f.sub.H of the recording and reproducing channel transfer function H(f) is higher than the cut-off frequency f.sub.11 of transfer function PR.sub.11 (f). If the waveform equalizer 4 is constructed with a transfer function E(f) that drops to zero at cut-off frequency f.sub.11 in this case, an error-free equalization state can, in principle, be achieved.
However, when the recording density is increased, the cut-off frequency f.sub.H of transfer function H(f) drops due to interwaveform interference, and becomes, as shown in FIG. 17, relatively lower than the cut-off frequency f.sub.11 of transfer function PR.sub.11 (f). In this case there is a region (f.sub.H .ltoreq.f.ltoreq.f.sub.11) wherein equation [8] is not satisfied, and equalization error increases in principle. An increase in equalization error means that correction of intersymbol interference weakens, and, thus, high density recording and reproducing is naturally limited.
(2) Even when the recording density is relatively low as shown in FIG. 16, the high band side of transfer function E(f) suggests a value or 1 or greater, and thus acts to emphasize noise. Furthermore, while it is possible to use delay circuits 4a with a short delay time and increase in hardware the number of taps to waveform equalizer 4 as a means of reducing equalization error (least square error), this will obviously increase the complexity of waveform equalizer 4, additive noise increases dramatically with the increase in the number of delay elements, and high band emphasis of noise occurs. This is, therefore, not a particularly effective means of suppressing equalization error. Conversely, the bit error rate increases, and the bit error rate is not significantly improved even after Viterbi decoding is applied.
Therefore, an object of the present invention is to provide an information recording and reproducing apparatus whereby high density recording can be improved and the bit error rate can be reduced by means of finding the optimum partial response method that can be combined with Viterbi decoding to achieve optimum performance from the overall system comprising the encoding circuit, recording and reproducing system, and demodulation circuit.